tbuckley/cabot-search huggingface dataset:
THE ROLE OF A GENOMICS CLINICAL NURSE SPECIALIST IN HELPING TO BUILD A PATHWAY FOR WHOLE GENOME SEQUENCING TO BE OFFERED TO NEURO-ONCOLOGY PATIENTS
Authors: Aeron Suarez, Victoria Hurwitz, Jessica La, Charlotte Robinson, Ellie Kostick, Sarah Hedges, Nicola Harding, Renata Fukuthi, Ana Dias, Anwar Alhaq, Barnaby Clark, Safa Al-Sarraj, Ross Laxton, Kelly Eggleton, Ranjeev Bhangoo, Keyoumars Ashkan, Richard Gullan, Francesco Vergani, Jose Pedro Lavrador, Cristina Bleil, Bassel Zebian, Lucy Brazil, Omar Al-Salihi, Angela Swampillai, Kazumi Chia, Vishal Manik
Journal: Neuro-Oncology (2023)

Abstract AIMS Whole genome sequencing is currently being offered to paediatric, teenage and young adult neuro-oncology patients and this was being managed by a genomics practitioner who works cross-site. We found that some patients are being discharged from the hospital without 1 component of the test or the consent. Our aim is to create a solid pathway in which fresh tissue, blood sample and record of discussion are taken at a certain stage in their hospital admission. METHOD A poster was created to remind the theatre team that a fresh tumour tissue and EDTA blood sample are the required samples to proceed with whole genome sequencing. Consent training is being provided to all clinical nurse specialists who look after CNS tumours in order to secure the record of discussion at any point in their hospital appointment. After several shadowing and doing the consenting process with supervision, they are expected to be able to be independent in doing this. RESULTS The clinical nurse specialist team have consented 24 out of 37 paediatric, teenage and young adult neuro- oncology patients that were operated since July 2022. Almost all of them have had their bloods taken intra- operatively with some taken whilst still an in-patient. CONCLUSIONS Whole genome sequencing will soon be offered to all neuro-oncology patients and the entire team will need to be equipped in securing the record of discussion in order for this test to proceed and this will be led by the clinical nurse specialist team.
DEMOGRAPHICS, GENETICS, AND EPIGENETICS INflUENCE THE LESION DISTRIBUTION OF GLIOMA
Authors: James Ruffle, Samia Mohinta, Sebastian Brandner, Harpreet Hyare, Parashkev Nachev
Journal: Neuro-Oncology (2023)

Abstract AIMS Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic innovation in neuro- oncology. Gliomas typically exhibit a spectrum of genetic mutations, reflecting multiple, potentially complex molecular interactions, and vary widely in their imaging appearances across size, morphology, texture, anatomical distribution, and many other spatial properties. This multifaceted diversity obscures the relationship be- tween tumour genotypic and imaging features, and their joint influence on disease evolution and treatment susceptibility. Though opaque to simple statistical methods, it may nonetheless be accessible to models with the expressivity to capture complex interactions between many different factors. METHOD Studying an international sample of 4064 IDH-wildtype glioblastoma, IDH-mutant oligodendroglioma and astrocytoma, deploying an in-house developed state-of-the-art lesion segmentation model, here we map the characteristic distribution of tumour tissue components across the brain and link their spatial properties lesion genetics and epigenetics. RESULTS We identify radical differences in tumour spatial topology related not only to diagnosis, but also age, sex, and genetic/epigenetic markers inclusive of TERT, EGFR, and MGMT methylation status. Lesions were equally common across left and right cerebral hemispheres, but significantly larger at presentation when right-sided (p&amp;lt;0.0001), indicating these lesions present later. Both glioblastoma and astrocytoma were commonly temporally based, though oligodendroglioma were often frontal. EGFR amplification was more common in right temporal lesions, whilst MGMT methylation and TERT appeared more bilateral. CONCLUSIONS Our results reveal the deep topological structure of gliomas, enabling richer, more closely individuating phenotyping, the development of more robust predictive models of treatment and prognosis, and illuminating multi- modal associations of potential mechanistic significance.
AUTOMATED VASARI FEATURE SET REPORTING FOR GLIOMAS IS EffCIENT AND EFFECTIVE
Authors: Faith Lee, James Ruffle, Samia Mohinta, Valeria Kopanitsa, Parashkev Nachev, Harpreet Hyare
Journal: Neuro-Oncology (2023)

Abstract AIMS The quantitative evaluation of gliomas using the VASARI MRI feature sets aims to facilitate consistent radiological reporting of gliomas but rarely done in clinical practice due to user variability in addition to technical and time constraints. We questioned whether deep-learning driven systems for automated VASARI feature derivation might resolve these issues, with comparison to neuroradiologist ground truths. METHOD VASARI imaging features were derived for 125 gliomas, both manually and using the automated model. Tumour segmentation models were constructed using 1251 patients from RSNA-BRATS with nnU-Net, and a processing pipeline developed within Python. The following features were compared: tumour location (F1); side of lesion (F2); proportion enhancing (F5); proportion non-enhancing (nCET) (F6); multifocal (F9); proportion edema (F14); ependymal extension (F19) and deep white matter (WM) invasion (F21). RESULTS The out-of-sample Dice performance for the tumour segmentation model was 0.945. Automated VASARI feature sets could be derived at a rate of under 0.5 seconds per patient. There was high concordance between manual and automatic segmentation in determining side of lesion (F2, 91.2%), ependymal extension (F19, 86.4%), anatomical tumour location (F1, 77.6%), deep WM invasion (F21, 65.6%) and proportion of enhancing tumour (F5, 54.4%; r=0.377, p&amp;lt;0.001). Automated segmentation overestimated proportions of edema (F14, 92.8%) and nCET (F6, 86.4%). CONCLUSIONS Automated VASARI feature set generation provides quick and accurate predictions however, proportions of oedema and non-contrast tumour were frequently over-estimated. Future empirical work will focus on optimization and further systematic evaluation of this automated pipeline for more accurate quantitative radiology reporting and corresponding clinical decision-making.
PREDICTING INPATIENT LENGTH OF STAY FOR PATIENTS UNDERGOING NEURO-ONCOLOGICAL OPERATIONS: A MACHINE LEARNING PERSPECTIVE FROM A 10-YEAR STUDY AT A NATIONAL TERTIARY NEUROSURGICAL CENTRE
Authors: Ella Snowdon, Sayan Biswas, Joshua MacArthur, Ved Sarkar, Callum Tetlow, K Joshi George
Journal: Neuro-Oncology (2023)

Abstract AIMS Length of stay (LOS) following neuro-oncological (NO) operations is essential information for both clinicians, patients and hospital administrators. This study aimed to analyse the LOS of patients following the most common NO surgeries over time and subsequently create a machine learning (ML) algorithm to predict LOS. METHOD Retrospective case series analysis of all NO operations at a tertiary neurosurgical centre from 2012 to 2022. A total of 4700 patients were identified and classified based on 40 operation types. 3 regression ML models were developed to predict the inpatient LOS: XGBoost Regressor, Huber Regressor and Support Vector Machine. Models were trained using 25 stratified KFold cross-validation with an 80:20 train-test split. All models were evaluated via model coverage score, mean absolute error (MAE), mean squared error (MSE) and root mean squared error (RMSE) metrics. All analysis was conducted in R and Python. RESULTS The average patient age was 53.5±15.7 years, with a mean overall LOS of 160.7hrs. The most common operation was an excision of lesion of brain with 2735 operations. The operation with the longest average LOS was extirpation of lesion of meninges of spinal cord at 268.9hrs, with the shortest being biopsy of lesion of brain at 48.1hrs. The best performing model was the XGBoost Regressor with a mean coverage score=0.885 [0.966, 0.803], RMSE=0.784, MAE=0.594, MSE=0.615. CONCLUSIONS ML models can accurately predict LOS and have potential for use in clinical practice to help clinical decision making. Further studies are needed to validate these models on prospective data and additional predictor variables.
RADIOLOGICAL SURVEILLANCE AFTER RESECTION OF LOW GRADE DYSEMBRYOPLASTIC NEUROEPITHELIAL TUMOUR AND GANGLIOGLIOMA: HOW OFTEN AND FOR HOW LONG?
Authors: Theodore Marples, Difei Wang, Tasneem Saumtally, Nida Kalyal, Istvan Bodi, Harutomo Hasegawa, Richard Selway
Journal: Neuro-Oncology (2023)

Abstract AIMS Prolonged follow-up with imaging has costs both financial and psychological. We sought to review clinical and radiological follow-up for operated dysembryoplastic neuroepithelial tumour (DNET) and ganglioglioma in our unit. METHOD Retrospective review of patients diagnosed with WHO grade 1 DNET or ganglioglioma identified from our histopathology database over the last 20 years. RESULTS 44 patients were identified (DNET n=23, ganglioglioma n=21). Mean age at first surgery was 27.2 and 22.3 respectively. The median length of follow-up was 3.45 (0.84-13.9) years for DNET, and 5.03 (0.4-12.6) years for ganglioglioma. The majority of the patients had epilepsy (39/44, 88.6%) prior to surgery. Patients with DNET had 0.58 postoperative scans per year, whilst those with ganglioglioma had 1.17 scans per year. 11 (47.8%) DNET and 9 (42.9%) ganglioglioma patients had residual tumour after first surgery. None of the DNET patients had radiological change during follow-up. 9 (43%) patients with ganglioglioma had radiological change noted at least once during follow-up. 3 (13%) patients with DNET and 4 (19%) with ganglioglioma had further surgery for ongoing seizures due to residual tumour, but not for radiological progression. CONCLUSIONS Radiological change following tumour resection did not occur for DNET whereas it was more common for gangliogliomas. A reduction in postoperative imaging in our practice could be considered for operated low grade DNET and ganglioglioma, given that for all patients the indication for reoperation was seizures rather than tumour progression.
INCIDENCE AND PREDICTORS OF CLINICALLY SIGNIfiCANT ACUTE AND LATE TREATMENT-RELATED TOXICITY AFTER STEREOTACTIC RADIOSURGERY IN 4 OR MORE BRAIN METASTASES
Authors: Shefali Parikh, Usha Alluri, Helen Benghiat, Geoff Heyes, Sara Meade, Vijay Sawlani, Swarupsinh Chavda, Colin Watts, Mitchell Hickman, Paul Sanghera
Journal: Neuro-Oncology (2023)

Abstract AIMS Selected patients with multiple brain metastases can benefit from stereotactic radiosurgery (SRS). Brain V12 (total brain volume receiving 12Gy including target) can predict for late toxicity in single target benign disease, however their value remains uncertain for multiple brain metastases. We report the incidence and evaluate predictors of toxicity in patients with 4 or more brain metastases treated with single fraction SRS. METHOD 226 patients with 2160 treated metastases from 2014-21 were retrospectively studied. Severe acute toxicity, and symptomatic late toxicity (new/progressive neurological symptoms ≥ 3 months post SRS) with MRI changes suggestive of treatment-effect were analysed. Kaplan-Meier method and cumulative incidence function was used to assess survival and toxicity respectively. RESULTS Median number of metastases per patient was 6 (range 4-41) and median V12 was 11.3cc (range 1.5- 45.2cc). Median overall survival (mos.) was 7.6 months. Absolute incidence of acute grade 3/4 cerebral oedema/haemorrhage was 4.9%. The subgroup developing late SRS-related toxicity (16 patients) had a higher mos. than those without toxicity (25mos vs 5 mos., p &amp;lt;0.002). 9/16 (56%) patients developed Grade 3 or 4 toxicity. 82/226 patients survived &amp;gt;12 months and cumulative incidence function of symptomatic SRS-related late toxicity in this group was 4% at 1 year and 9.5% at 2 years. CONCLUSIONS Within the limits of data available a brain V12 value did not meaningfully predict for late SRS related toxicity in patients with multiple brain metastases. The cumulative incidence of clinically relevant late toxicity remains &amp;lt;10% at 2 years despite accepting a high median V12 to treat these patients.
SURVIVAL OUTCOMES AFTER WHOLE BRAIN RADIOTHERAPY
Authors: Andrew Ho, Farasat Kazmi, Hannah Hendry, Pinelopi Gkogkou
Journal: Neuro-Oncology (2023)

Abstract AIMS Cerebral metastases from extra-cranial primary cancer carries a poor prognosis. For patients in whom surgical resection or SRS are not suitable, local control rates are poor. There is considerable debate surrounding the value of whole brain radiotherapy in this patient cohort in terms of local control, survival and functional status. We aimed to measure survival in patients receiving whole brain radiotherapy at the Norfolk and Norwich University Hospital. METHOD All patients who completed a course of whole brain radiotherapy at our centre between April 2018 and December 2022 were retrospectively analysed. Patients who were receiving prophylactic cranial irradiation of small cell lung cancer were excluded. Baseline demographics, oncologist declared ECOG performance status at referral for treatment, radiotherapy dose and survival were recorded. RESULTS 88 patients received WBRT during this period. The median follow-up interval was 85 days. 12 patients received 30 Gy in 10 fractions, 59 received 20 Gy in 5 fractions and 17 received 12 Gy in 2 fractions. The median overall survival following completion of radiotherapy was 85 days. At 6 weeks after radiotherapy, 23.9% of patients had died. Univariate analysis with Cox proportional hazards model did not demonstrate a significant hazard ratio for age (&amp;lt;65 or ≥65), ECOG performance status or radiotherapy dose. CONCLUSIONS Survival following whole brain radiotherapy remains poor. In particular, almost a quarter of patients are not alive 6 weeks after treatment. This is particularly pertinent given the anticipated trajectory of acute toxicities from treatment.
EXTRACELLULAR VESICLES TRANSFER RESISTANCE TO VINCRISTINE IN SONIC HEDGEHOG MEDULLOBLASTOMA
Authors: Philippa Wade, Alistair Hume, Ian Kerr, Beth Coyle
Journal: Neuro-Oncology (2023)

Abstract AIMS • To determine the expression patterns of specific ATP-binding cassette (ABC) transporters in medulloblastoma • To assess whether ABC transporters play a role in acquired drug resistance in SHH medulloblastoma using drug-tolerant cell line models • To assess whether extracellular vesicles transfer drug-tolerance in SHH medulloblastoma and determine the mechanism by which they do this METHOD Drug-tolerant cell lines were generated by continuous culture in drug-containing culture medium. ABC trans- porter gene and protein expression was assessed via qPCR and western blot. EVs were isolated from EV-depleted medium using size-exclusion chromatography. Nanoparticle tracking analysis was used to quantify and deter- mine size. Cytotoxicity analysis was used to determine EV-mediated transfer of resistance in the presence or absence of an ABC transporter inhibitor. RNA sequencing of EVs from matched vehicle and drug tolerant cell lines was carried out. RESULTS Analysis of drug-tolerant cell lines revealed significant increases in specific drug transporter gene expression across medulloblastoma subgroups. ABCB1 protein expression was significantly higher in drug-tolerant sonic- hedgehog (SHH) lines and inhibition of ABCB1 in a drug-tolerant SHH line abolished acquired resistance to vincristine. Cytotoxicity assays on sensitive cells, after pre-treatment with drug-tolerant EVs, showed a significant increase in vincristine resistance, implicating EVs in the transfer of resistance. CONCLUSIONS Data to date supports the hypothesis that multidrug transporter carrying extracellular vesicles may transfer their multidrug resistant phenotype to surrounding cells in medulloblastoma. We are currently testing this using inhibitors and knockout lines, in addition to RNA sequencing, with the hopes of providing new therapeutic targets to patients with medulloblastoma.
IMAGING HABITAT CHANGES AFTER PREOPERATIVE RADIOTHERAPY FOR GLIOBLASTOMA: UTILISATION OF A BIOINFORMATICS AND MACHINE LEARNING PIPELINE TO CHARACTERISE REGIONAL TREATMENT RESPONSE
Authors: Mueez Waqar, Petra Van-Houdt, Eline Hessen, Daniel Lewis, Ka-loh Li, Xiaoping Zhu, Alan Jackson, Mudassar Iqbal, Federico Roncaroli, Ibrahim Djoukhadar, David Coope, Gerben Borst
Journal: Neuro-Oncology (2023)

Abstract AIMS Imaging of tumour habitats is a novel technique to assess regional treatment response by defining tumour ‘habitats’, which are regions with shared imaging characteristics. Here, we describe a novel pipeline to characterise imaging habitats in glioblastoma using bioinformatics and machine learning. We apply this pipeline to glioblastoma patients in the Preoperative Brain Irradiation in Glioblastoma (POBIG) trial that received preoperative radiotherapy for the first time. METHOD Glioblastoma patients underwent preoperative diffusion/perfusion MRI. A two- stage clustering pipeline was developed to define imaging habitats using relative cerebral blood volume (rCBV) and apparent diffusion co- effcient (ADC). 6 habitats were defined that occupied 10.6-21.5% of tumour volume. Treatment response was evaluated using Ktrans permeability. RESULTS In newly diagnosed cases the commonest habitats included those with a medium and high rCBV. In contrast, recurrent cases had significantly greater proportion of low rCBV habitats (p = 0.026). Two patients in the POBIG trial received 8 Gy preoperative radiotherapy. Within 24 hours of treatment there was a global decrease in vascularity with a decrease in high rCBV habitats (-3.7%) and increase in low rCBV habitats (+8.2%) in irradiated regions. Habitats demonstrated a heterogeneous response to preoperative radiotherapy, with a greater increase in Ktrans in high rCBV habitats (mean +83%) versus low rCBV habitats (mean +40%). CONCLUSIONS We have developed a unique pipeline to delineate imaging habitats in glioblastoma and applied it to a novel trial. Imaging habitats can allow regional monitoring of treatment response and could allow more targeted treatment in future.
A RANDOMISED TRIAL TO OPTIMISE OUTCOMES IN PATIENTS WITH BRAIN METASTASES (AROMA): TRIAL PROPOSAL
Authors: Andrew Ho, Lillie Pakzad-Shahabi, Jiarong Chen, Matthew Williams
Journal: Neuro-Oncology (2023)

Abstract AIMS Brain metastases carry significant morbidity and mortality. The survival of patients with metastatic disease has improved due to systemic therapy advances conferring greater extracranial control. Optimal intracranial local control is probably surgical resection or stereotactic radiosurgery. However, there is a cohort for whom this is inappropriate, either for disease or patient fitness reasons. Traditionally, treatment has included whole brain radiotherapy although this has not been convincingly shown to improve survival or quality of life. AROMA is a single-arm phase II study investigating the feasibility of delivering a novel radiotherapy technique and measuring quality of life. METHOD We have developed a modern technique to deliver dose-escalated internal PTV (DE-iPTV) in patients with metas- tases too large for SRS. Our previously-published planning study demonstrates dosimetric improvements in 5 fractions versus WBRT, with higher lesion dose and lower normal tissue dose. It is delivered using a standard linear accelerator. In AROMA, patients for whom their oncologist would normally consider WBRT instead receive DE-iPTV. QoL measures (EQ5D-3L, Barthel, PS) are collected weekly for 8 weeks then monthly to 6 months. There is an MRI at 6 weeks post-radiotherapy. We are also collecting retrospective observational data on participating centres’ WBRT cohort. RESULTS The primary outcome is completion of treatment and completion of QoL at 8 weeks. Secondary outcomes include lesional response, survival, QoL and steroid use. CONCLUSIONS AROMA is a phase II study looking at the feasibility of DE-iPTV for patients with brain metastases not suitable for SRS or neurosurgery. It is currently in the design and setup phase.
CLIC1 ION CHANNELS AS BIOELECTRIC TARGETS FOR TTFIELDS IN PAEDIATRIC HIGH-GRADE GLIOMA
Authors: Michaela Griffn, Paul Smith, Raheela Khan, Stuart Smith
Journal: Neuro-Oncology (2023)

Abstract AIMS Develop and validate a comprehensive understanding of CLIC1 and its prognostic significance, coupled with a functional analysis in pHGG cells. To develop electrical and pharmacological methods of manipulating CLIC1 for combination with TTFields METHOD Chloride Intracellular Channel (CLIC) channel expression patterns were identified via RNA sequencing of in- house patient tissues. siRNA depletion of CLIC1 and CLIC4 was assessed using functional assays, alone and in combination with TTFields and or CLIC inhibitor. Whole transcriptome gene expression analysis (Human Clairom™ Array) of pGBM cells treated with TTFields was carried out. Whole cell and cell attached patch clamp protocols were used to assess ion channel activity in pHGG. RESULTS CLIC1 deficiency was associated with increased overall survival(p=&amp;lt;0.003). siRNA depletion propagates a re- duction in the proliferation, migration and invasion of pHGG cells, associated with cell cycle arrest. CLIC1 deficiency exacerbated the effect of TTFields, reducing clonogenic and proliferative capabilities. Combination of metformin and TTFields increased the sensitivity of cells to TTFields. Whole transcriptome gene expression analysis found that cells treated with TTFields exhibited a down-regulation in CLIC1 compared to untreated cells, with tolerance to long-term TTFields treatment being associated with recovery of CLIC1 expression. CONCLUSIONS These data provide rationale that genetic, electrical, and pharmacological manipulation of CLIC1 can reduce the capacity of childhood brain tumours to proliferate and invade. TTFields treatment results in a dysregulation of CLIC channel expression and function, and combination with CLIC inhibitions demonstrates a synergistic effect. CLIC channels may be a suitable target for combination therapy to enhance the treatment effcacy of TTFields.
PROCARBAZINE, LOMUSTINE, VINCRISTINE FOR THE SECOND LINE TREATMENT OF GLIOBLASTOMA MULTIFORME
Authors: Cecilia McCormick, Pinelopi Gkogkou, Andrew Ho
Journal: Neuro-Oncology (2023)

Abstract AIMS Most patients with glioblastoma recur despite surgery and post-operative chemoradiation. The optimal second line chemotherapy regime is not known. The aim of this study was to evaluate PCV chemotherapy given as second line treatment for glioblastoma. METHOD Data was collected for all patients with glioblastoma treated with second line PCV between 2009 and 2021 at the Norfolk and Norwich University Hospital. All underwent surgical resection either complete or incomplete resection followed by adjuvant radiotherapy and chemotherapy according to the Stupp or Perry A protocol. All received palliative PCV chemotherapy at recurrence. The Response Assessment in Neuro-Oncology (RANO) criteria were used to assess response to palliative PCV chemotherapy. Patient and disease related characteristics were described. Disease free survival from recurrence to death and survival outcomes were estimated using Kaplan-Meir method. RESULTS 70 patients were evaluated. Overall survival from surgery to death was 290 days (95%CI 245 to 318) Survival from disease progression to death was 182 days (95%CI 131 to 218). Subgroup analysis was performed for patients &amp;lt;65years and &amp;gt;65years. For patients &amp;lt;65 years N=51, median overall survival was 199 days (95%CI 142 to 353) p value 0.1246. For those &amp;gt;65 years N=16, median overall survival was 130.5 days (95%CI 93 to 227) CONCLUSIONS Using PCV as a second line chemotherapy for patients with glioblastoma is a reasonable approach. It is well tolerated and provides benefit for patients &amp;lt;65 years as well as older patients.